Abstract
The performance of military equipment keeps improving, and troops are equipped with more and more sophisticated weapons and equipment, highlighting the importance of equipment maintenance and support. Without strong equipment support capability, it is impossilbe to cope with the fast-paced and high-intensity modern warfare, and to effectively give play to the role and advantages of equipment systems integration. Therefore, it is of great significance to have a profound study of and improve the equipment support capability assessment method. Based on requirement analysis, we built an equipment support capability assessment indicator system of the Army Digital Medium-sized Synthetic Brigade in cross-domain operations. The weight of the assessment indicator system was determined using the AHP analytic hierarchy process. The equipment support capability assessment model was constructed. With the data obtained from the exercises using real equipment and system-of-systems (SoS) countermeasure simulation tests, we completed the assessment of the equipment support capability of the Synthetic Brigade using neural network algorithms.
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